Examining the mediating role of muscle quantity in adolescents: associations with adiposity, cardiorespiratory fitness, muscular fitness, and cardiometabolic risk factors

The aim of this study was to evaluate the mediation role of muscle quantity in the relationship between physical fitness and cardiometabolic risk factors (CMRF) in adolescents. This cross-sectional study conducted with 120 adolescents of both sexes, aged between 10 and 17 years. Body mass, height, fat mass (FM), lean mass, blood pressure, high-density lipoprotein, low-density lipoprotein, triglycerides, glucose, insulin, cardiorespiratory fitness (CRF) and 1 repetition maximum strength (1-RM) with evaluation of the leg press 45° (RM-leg), bench press (RM-bench) and arm curl (RM-arm). Body mass index z-score, appendicular skeletal muscle mass, appendicular skeletal muscle mass index, lean mass index (LMI), muscle-to-fat ratio (MFR), age at peak height velocity, and CMRF z-score were calculated. The direct relation between FM and CMRF was mediated by the LMI (26%) and inverse relation between CRF and CMRF was mediated by the LMI (26%). For girls, the direct relation between FM and CMRF was mediated by the LMI (32%); the inverse relation between CRF, RM-leg, RM-arm and CMRF was mediated by the LMI (32%, 33%, and 32%, respective). For boys, the indirect effect was not significant, indicating that LMI is not a mediator in the relation between FM, CRF, 1-RM with CMRF. The direct relation between RM-leg and CMRF was mediated by the MRF (16%). This finding evidenced the importance of promoting a healthy lifestyle to improve physical fitness levels and the quantity of muscle mass in adolescents.


Study design and population
This is a cross-sectional study with a correlational descriptive character.The population consisted of adolescents from Curitiba and the Metropolitan Region-Paraná/Brazil.The recruitment was conducted in a non-probabilistic sampling process, for convenience.Adolescents, parents and/or guardians were informed about the research procedures and signed informed consent form.Data collection was conducted between March and April 2019.
This study recruited 231 adolescents and included 120 adolescents of both sexes, aged between 10 and 17 years, who participated in all assessments.Sample size was calculated a priori using the G*Power software, through the linear regression, with four predictive variables.Power of 0.90, an alpha of 0.05, and effect size (f) of 0.15 were assigned.Based on these criteria, the minimum sample size was 108 participants.The inclusion criteria were: (a) participate in all assessments; (b) no present contraindications to the tests, including the absence of heart, pulmonary and osteoarticular diseases; and (c) not using drugs that interfere with research results.

Anthropometric measures
Measurements were performed according to the procedures described in the literature 28 .Height was measured using a portable stadiometer (Avanutri®) with an accuracy of 0.1 cm, and body mass was measured using a digital reading platform scale (Welmy®), with a maximum capacity of 200 kg and an accuracy of 0.1 kg.Body mass index z-score (BMI-z) were calculated in the WHO Anthro Plus® 29 .Waist circumference measurement was evaluated with a flexible and inextensible tape with a resolution of 0.1 cm (Sanny®) 28 . www.nature.com/scientificreports/

Dual energy X-ray absorptiometry
For the analysis of body composition, dual energy x-ray absorptiometry (DXA) was performed with a Hologic QDR® model 4500 device and the information was analyzed by the equipment software.For the examination, the adolescents wore appropriate clothing and were asked to remove any jewelry or metallic accessory from the body that could interfere.After, they should down in dorsal decubitus on the equipment table.Scanning was conducted from the upper region of the skull to the ends of the toes and lasted approximately two to five minutes.Fat mass, lean mass, lean arms mass, lean legs mass, were determined with a resolution of 1 g and described in kg.

Muscle quantity
Appendicular skeletal muscle mass (ASM) was calculated as the sum of lean mass from arms and legs (kg).Appendicular skeletal muscle mass index (ASMI) was calculated as the ASM divided by height squared (kg m −2 ) 30 .Lean mass index (LMI) was calculated as lean mass divided by height squared (kg m −2 ) 31 .Muscle-to-fat ratio (MFR) was calculated as total lean mass divided by total fat mass (kg) 19 .

Clinics and metabolic variables
Systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured using a previously calibrated mercury sphygmomanometer, with the appropriate cuff size for the arm circumference, with the adolescent sitting and right arm supported at heart level, after resting for ten minutes.Two measurements were performed at a 1-min interval, with the lowest value being considered 32 .Blood samples were collected in the morning by specialists using standard techniques after twelve hours of fasting.The colorimetric enzymatic method was used to measure high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), triglycerides (TG) and insulin.The chemiluminescence method was used to determine glucose.Homeostasis metabolic assessment insulin resistance (HOMA-IR) 33 and quantitative insulin sensitivity check index (QUICKI) 34 were determined.Cardiometabolic risk factors (CMRF) score was calculated (z-score): SBP + DBP + HDL-c + LDL-c + TG + HOMA-IR.HDL-c was multiplied by −1 .This approach was used in similar studies 35,36 .

Cardiorespiratory fitness
Peak oxygen consumption (VO 2peak ) was assessed using the maximum incremental test, on a treadmill, using a K4b 2 metabolic analyzer (Cosmed®).A warm-up was performed with a five-minute walk of 2.7 km h −1 .Protocol started at a speed of 4.0 km h −1 , a progressive increase of 0.6 km h −1 every minute and a constant and fixed inclination of 1%.After the test is completed, a walk at 5.0 km h −1 was performed, reduction of 1.0 km h −1 every minute for three minutes.A heart rate monitor (Polar®) was used to determine the maximum heart rate (HR max ).Test was considered maximum when two of the criteria were observed: (a) exhaustion or inability to maintain the required speed 37 ; (b) respiratory exchange ratio ≥ 1.0; (c) achieving the HR max predicted 38 .
The VO 2peak was determined after filtering in 15 s intervals and identified by the highest value obtained after the VO 2 plateau.Values of VO 2 increase < 50 mL/min −1 in the last 30 s of the stress tests were interpreted as a VO 2 plateau.VO 2peak was expressed in absolute units (L min −1 ) and relative to body mass (mL kg min −1 ).All assessments were carried out by two trained evaluators in a controlled environment in which the ambient temperature varied between 20 and 25 °C and the relative humidity between 40 and 60%.

Muscular fitness
Maximum strength was measured by the one-repetition maximum test (RM) 20 .Exercises used were leg press 45° (RM-leg press), bench press (RM-bench press) and arm curl (RM-arm curl), performed in three sessions, with an interval of 48 h between each session.In session 1, familiarization was performed, with three sets of eight to ten repetitions with progressive loads to reach approximately 50% of the load.Session 2, a series of eight repetitions began with approximately 50% of the perceived load in session 1.After a one-minute of rest, the second series of three repetitions was performed at 70% of the perceived load, and after two minutes of rest, were submitted to the RM test with 100% of the perceived load.If successfully executed, 5-10% of the load was added until reaching the maximum load with a rest of three to five minutes.When not successfully executed, it reduced 50% of the increment of the last attempt.In session 3, the test followed the same procedure as in session 2, with the aim of confirming the previous load or carrying out new increments, if necessary.The highest load achieved between sessions 2 and 3 was considered for analysis.

Covariates
Sex, chronological age, somatic maturation, and fat mass are considered covariates.Adolescence is a period of somatic and biological growth, and so that these changes do not confound the results, the analyses were controlled considering somatic maturation.Somatic maturation was estimated by determining the distance in years from peak height velocity by the mathematical model based on height, age, and sex.Prediction of age at peak height velocity was determined by subtracting the maturity offset from the chronological age (years) 39 .

Statistical analysis
Shapiro-Wilk test was used to verify the normality of the data.Standard descriptive statistics were used to characterize the sample.For analysis purposes, three groups were defined by BMI-z: Eutrophic (score < 1), Overweight (between score ≥ 1 and < 2) and Obese (score ≥ 2).Comparisons between groups were verified by one-way analysis of variance with Bonferroni's post-hoc for parametric variables and the Kruskal-Wallis for non-parametric.Spearman's correlation coefficient was used to verify relationships.www.nature.com/scientificreports/Mediation analysis was determined from linear regression models (bootstrapping procedures, 10,000 resamplings; 95% IC BCa).This approach considered muscle quantity independent variable, CRF and muscular fitness as mediators, and cardiometabolic risk factors as dependent variables.Mediation models were constituted: equation (a) independent variable by the mediator; equation (b) mediator by the dependent variable; equation (c) independent variable by the dependent variable (total effect); and equation (c′) independent variable and mediator by the dependent variable (direct effect).The indirect effect was estimated by ab equations, and it was significant if zero was outside the 95% CI 40 .The percentage of mediation was estimated as 1 − (c′/c).Analyzes were adjusted for sex, age, age at peak height velocity and fat mass.Data analysis was performed with the SPSS v.24.0, the moderation models in the PROCESS macro for the SPSS, and the significance level was established at p ≤ 0.05.

Consent to participate
Parents and/or guardians and adolescents signed the terms of consent for participation in the research.

Informed consent
Informed consent was obtained from all participating teams in the study.

Results
Descriptive characteristics of the adolescents separated by sex and allocated by BMI-z are summarized in Table 1.In the total sample, age, MFR and QUICKI were higher in eutrophic, while fat mass, lean mass, LMI, systolic blood pressure, triglycerides, insulin, HOMA-IR, and RM-leg press were higher in obese.No differences were found for the other variables (data not presented).For boys, age, MFR and QUICKI were higher in eutrophic, while waist circumference, fat mass, LMI, insulin, HOMA-IR were higher in obese.For girls, MFR and QUICKI were higher in eutrophic, while waist circumference, fat mass, lean mass, ASMI, LMI, insulin, HOMA-IR, VO 2peak , RM-leg press, and RM-arm curl were higher in obese.In the total sample, the CRMF was associated with muscle quantity and physical fitness, except RM-bench press.For boys, the CMRF was only associated with LMI and MRF.For girls, the CMRF was associated with ASM, LMI, and MRF, as well as VO 2peak , RM-leg press and RM-arm curl (Table 2).
Regarding the mediation analyses, the indirect effect was significant, indicating LMI mediation in the relationship between fat mass and CMRF, as well as between CRF and CMRF for the total sample (Fig. 1).In the analyses of boys, the indirect effect was not significant, indicating that LMI is not a mediator in the relationship between fat mass, CRF, RM with CMRF (Fig. 2).In the analyses of girls, LMI mediation in the relationship between fat mass and CMRF, as well as between CRF, RM-leg press, RM-arm curl and CMRF (Fig. 3).MFR mediation in the direct relationship between RM-leg press and CMRF (Fig. 4).

Discussion
In this study, the main findings indicate that muscle quantity shows a 26% mediation between CRF and CMRF in the total sample, whose relationship is most evident for girls (32%).LMI mediates 32% between fat mass and CRMF.Regarding MFR, a 16% mediation effect was observed between RM-leg press and CMRF, being found as 25% in boys and 22% in girls.However, the other indicators of muscle quantity assessed by the appendicular skeletal results, both ASM and ASMI showed no mediating effect in the analyses performed.Therefore, LMI and MFR seem to be better mediators of muscle quantity in adolescents between the variable's adiposity, cardiorespiratory and muscular fitness with the CRMF.To the best of our knowledge, this is one of the first studies to examine the mediating role of muscle mass quantity in the relationship between physical fitness and cardiometabolic risk score in adolescents.
The importance of our study is emphasized, since there is an inverse relationship between cardiometabolic risk and low muscle mass or disproportionate muscle mass (in relation to fat) 15,16 .The disproportionate between of fat and lean mass was mainly analyzed in the context of adults, the elderly, and/or those with chronic diseases 15 .In the elderly, this relationship is confirmed by the amount of ASM (kg) divided by the squared height (m −2 ), while for adults, the diagnosis is made by the ratio of ASM (kg) divided by BMI (kg/m −2 ), whose adjustment is intended to reduce the interference that weight may have on lean mass 30 .For youth, proposals for verifying muscle quality include the ratio of muscle mass and fat mass or MFR 41 , handgrip 42,43 and LMI 31 .Thus, Ripka et al. 31 conducted a study that established curves with percentiles for fat mass, lean mass, LMI, ASM by DXA for Brazilian adolescents.They proposed LMI values of the 3rd percentile as the lower limit, aiming to identify LM abnormalities in the 12-to 17-year-old age group, which can be used for the diagnosis of decreased lean mass and relate to cardiometabolic risk, especially in overweight adolescents.Thus, excess fat mass in relation to muscle mass may be associated with low muscle mass, by reduced strength (i.e.dyapenia), as well as reduced muscle function related to cardiometabolic factors, which usually accompany obesity.
In the present research, in the comparison between adiposity groups by BMI-z, we confirmed that body weight overload exerted daily muscle work in adolescents with obesity, demonstrated by higher LM and LMI, as well as higher RM-leg press compared to eutrophic and overweight adolescents.While the ASM and ASMI did not differ between the groups, denoting no discrimination of muscle quantity in adolescents.However, it is reinforced that we did not evidence the presence of disproportion between fat and lean mass in adolescents with obesity in the current study, whose LMI values were above the 3rd percentile 31  In other studies, adolescents with obesity also demonstrated greater absolute muscle strength compared to their non-obese peers, but showed low muscle strength relative to body mass, low muscle fitness, and reduced neuromuscular activation capacity 14,16,44 .Adolescents with obesity can compensate for their greater body weight by increasing the level of voluntary activation during muscle contraction 45 , which may reflect in positive adaptation of the neuromuscular system to weight-bearing tasks.However, adolescents with obesity exhibit higher energy expenditure in performing body movement and increased muscle fatigue rate during exercise, partially explaining their limited involvement in physical activities, reduced muscle fitness and mobility 46 .Therefore, they may have difficulty maintaining muscle strength due to being overweight and possibly cause muscle weakness, which in turn may be caused by reduced mobility, neural adaptations, and changes in muscle morphology.
In our study, in the analysis of the MFR we noticed that it was higher in eutrophic, whose indexes were followed in a decreasing manner by the overweight and then in the obese, because the advantage of the higher LM may present progressive impairment caused by the higher fat mass.However, adolescents with obesity showed    47 , disorders in lipid metabolism 47 , in glucose metabolism 48 and in the inflammatory process 47 .This can lead to the development of chronic diseases such as type 2 diabetes mellitus, non-alcoholic fatty liver disease, endothelial dysfunction, and musculoskeletal dysfunction in adulthood 49,50 .
Recent evidence has shown that dyapenia and muscle mass contribute to adverse cardiometabolic health outcomes in children and adolescents 51 .In Korean adolescents, low skeletal muscle mass was associated with metabolic syndrome, and even after controlling for confounding factors, the risk of metabolic syndrome was higher in adolescents with low muscle mass 49 .An observational study found that adolescents at the 25th percentile of muscle mass had higher waist circumference, blood pressure, triglycerides, TC/HDL-c, HOMA-IR, and metabolic syndrome z-score than their peers at other percentiles, as well as adolescents with low muscle mass and obesity had the most unfavorable cardiometabolic profile 52 .
Research suggests that a body composition phenotype, which combines high-fat mass and low muscle mass, may be associated with higher health risks in adults, compared to any one body composition compartment alone 53,54 .The underlying mechanisms by which obesity affects skeletal muscle remain poorly understood; however, lipid accumulation in skeletal muscle and chronic low-grade inflammation may contribute to muscle impairment 44 .The positive energy balance leads to excessive fat accumulation in the subcutaneous region and between skeletal muscle fibers 55 .Fat accumulation initiates a systemic inflammatory response characterized by infiltration of immune cells into skeletal muscle tissue and increased secretion and activation of pro-inflammatory cytokines by myocytes and adipocytes.Because of chronic exposure to pro-inflammatory cytokines, satellite cell function may be affected, as well as myoblast proliferation and differentiation, negatively impacting skeletal muscle maintenance and regeneration 56 .
In addition to muscle mass, muscle strength is also an important aspect of physical fitness 14,44 , a protective factor of physical and cardiometabolic health both in the adult and elderly population 8 and in children and adolescents 16,23 .These studies suggest that both low muscle mass and low muscle strength are contributors to metabolic dysfunction in the pediatric population 25 , as well as early onset of hypertensive measures 26 .Recent evidence focuses on reduction in muscle mass and cardiometabolic changes 16,23 , as well as understanding the mediating role of muscle quantity in the relationship between adiposity and bone mineral content 27 .Furthermore, although the interaction between reduced muscle mass and associated morbidities have not been investigated in detail in children and adolescents, excess fat with low muscle mass probably arises in childhood, reducing mobility and agility in children and adolescents 12 , and consequently compromising motor competence in adolescents with obesity 11 and metabolic health before adulthood 57 .
This study has some strengths and limitations.The strengths were to assess body composition by DXA, cardiorespiratory fitness by stress test with metabolic analyzer, and muscular fitness by the one repetition maximum test, considered the best methods for assessing physical fitness.We used some variables to compose a cardiometabolic risk score and were performed by valid and reliable methods for monitoring the adolescent's health.Also, adolescence is a period of somatic and biological growth, and changes can confound the results, our analyses were controlled for sex, age, and somatic maturation (age at peak height velocity).Finally, as far as we know, this study may be the first to consider LMI as a mediator in the relationship between physical fitness and a relevant marker of cardiometabolic health.On the other hand, we consider the cross-sectional design as one of the limitations, for not allowing the inference of causality, as well as the sample size used does not allow the generalization of the results, factors that should be analyzed with caution.
The results found in this study provide data on the association of muscle quantity, physical fitness, and cardiometabolic risk in adolescents, factors that contribute to the prevention and maintenance of health in this population.We highlight that LMI was identified as a mediator of muscle quantity in the relationship between fat mass vs. CMRF in total adolescents, plus CRF vs. CMRF in girls, who generally have lower participation in regular physical activity.While in boys there was no significant relationship between adiposity, physical fitness and CRMF.In addition, the MFR showed a mediating role in the relationship between RM-leg press and CMRF.Therefore, we highlight the importance of muscle quantity as a mediator in physical fitness and fat mass, for the reduction of cardiometabolic risk factors, justifying the importance of a healthy lifestyle in children and adolescents, especially with emphasis on girls. https://doi.org/10.1038/s41598-024-61805-w

Figure 1 .Figure 2 .
Figure 1.Mediation of lean mass index in the relationship between physical fitness and cardiometabolic risk for the total sample.All analyzes were controlled by sex, age, age at peak height velocity and fat mass.FM fat mass, CRF cardiorespiratory fitness, RM-leg repetition maximum-leg press, RM-bench repetition maximumbench press, RM-arm repetition maximum-arm curl, LMI lean mass index, CMRF cardiometabolic risk factors score, *significance p ≤ 0.05.

Figure 3 .
Figure 3. Mediation of lean mass index in the relationship between physical fitness and cardiometabolic risk in girls.Analyzes were controlled by age, age at peak height velocity and fat mass.CRF cardiorespiratory fitness, RM-leg repetition maximum-leg press, RM-bench repetition maximum-bench press, RM-arm repetition maximum-arm curl, LMI lean mass index, CMRF cardiometabolic risk factors score, *Significance p ≤ 0.05.

Figure 4 .
Figure 4. Mediation of muscle-to-fat ratio in the relationship between muscular fitness and cardiometabolic risk separated into all, boys, and girls.Analyzes were controlled by age and age at peak height velocity.RM-leg repetition maximum-leg press, MFR muscle-to-fat ratio, CMRF cardiometabolic risk factors score, *Significance p ≤ 0.05.
CRF similar to eutrophic adolescents, in which muscle quantity, represented by LMI and MFR, played a mediating role in the reduction of CMRF.

Table 1 .
Descriptive characteristics (mean ± standard deviation) of the adolescents separated by sex (boys and girls) and BMI-z.PHV peak height velocity, ASM appendicular skeletal muscle mass, ASMI appendicular skeletal muscle mass index, BP blood pressure, HDL-c high density lipoprotein, LDL-c low density lipoprotein, HOMA-IR homeostasis model to assessment insulin resistance, QUICKI quantitative insulin sensitivity check index, VO 2peak peak oxygen consumption, RM repetition maximum, ǂ Nonparametric test, a Different from obese, b Different from overweight), bold (significance p ≤ 0.05).